Chapter 6. Applying MapReduce patterns to big data
This chapter covers
- Learning how to join data with map-side and reduce-side joins
- Understanding how a secondary sort works
- Discovering how partitioning works and how to globally sort data
With your data safely in HDFS, it’s time to learn how to work with that data in MapReduce. Previous chapters showed you some MapReduce snippets in action when working with data serialization. In this chapter we’ll look at how to work effectively with big data in MapReduce to solve common problems.
If you want to understand the mechanics of Map-Reduce and how to write basic MapReduce programs, it’s worth your time to read Hadoop in Action by Chuck Lam (Manning, 2010).